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Application of Geometric Dependency Analysis to the Separation of Convolved Mixtures

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Independent Component Analysis and Blind Signal Separation (ICA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3195))

Abstract

We investigate a generalisation of the structure of frequency domain ICA as applied to the separation of convolved mixtures, and show how a geometric representation of residual dependency can be used both as an aid to visualisation and intuition, and as tool for clustering components into independent subspaces, thus providing a solution to the source separation problem.

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References

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Author information

Authors and Affiliations

  1. Centre for Digital Music, Queen Mary, University of London, UK

    Samer Abdallah & Mark D. Plumbley

Authors
  1. Samer Abdallah
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  2. Mark D. Plumbley
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Editor information

Editors and Affiliations

  1. Dept. of Architecture and Computer Technology, University of Granada, Spain

    Carlos G. Puntonet  & Alberto Prieto  & 

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© 2004 Springer-Verlag Berlin Heidelberg

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Abdallah, S., Plumbley, M.D. (2004). Application of Geometric Dependency Analysis to the Separation of Convolved Mixtures. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_69

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_69

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23056-4

  • Online ISBN: 978-3-540-30110-3

  • eBook Packages: Springer Book Archive

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